Tessellated Wasserstein Auto-Encoders. - Kuo Gai; Shihua Zhang (CoRR, 2020)

A Mathematical Principle of Deep Learning: Learn the Geodesic Curve in the Wasserstein Space. - Kuo Gai; Shihua Zhang (CoRR, 2021)

Progressive Feedforward Collapse of ResNet Training. - Sicong Wang; Kuo Gai; Shihua Zhang (CoRR, 2024)

Analytical Solution of a Three-layer Network with a Matrix Exponential Activation Function. - Kuo Gai; Shihua Zhang (CoRR, 2024)

OTAD: An Optimal Transport-Induced Robust Model for Agnostic Adversarial Attack. - Kuo Gai; Sicong Wang; Shihua Zhang (CoRR, 2024)

Matrix normal PCA for interpretable dimension reduction and graphical noise modeling. - Chihao Zhang 002; Kuo Gai; Shihua Zhang (Pattern Recognit., 2024)

Tessellating the Latent Space for Non-Adversarial Generative Auto-Encoders. - Kuo Gai; Shihua Zhang (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

On Pseudospectral Concentration for Rank-1 Sampling. - Kuo Gai; Bin Shi (CoRR, 2025)